Alibaba's GALA: Aligning Multimodal Features with RL to Boost Recommendations
_reachsumit · x · 2026-08-03
Alibaba's Taobao Shangou team proposed the GALA framework to tackle the challenge of effectively fusing multimodal signals with user behaviors in food delivery recommender systems.
- Core Innovation: Introduces an intermediate "generative RL alignment" stage using GRPO into the traditional two-stage training, refining multimodal embeddings dynamically with conversion-based rewards to align with actual purchase behaviors.
- Three-Stage Pipeline: Behavior-aware triplet pretraining -> Generative RL alignment -> Downstream fine-tuning, bridging the gap between semantic understanding and user behavior patterns.
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